L. Mendoza et Er. Alvarez-buylla, Genetic regulation of root hair development in Arabidopsis thaliana: A network model, J THEOR BIO, 204(3), 2000, pp. 311-326
The root epidermis of Arabidopsis thaliana is formed by alternate fries of
hair and non-hair cells. Epidermal cells overlying two cortex cells eventua
lly develop a hair, while those overlying only one cortex cell do not. Here
we propose a network model that integrates most of the available genetic a
nd molecular data on the regulatory and signaling pathways underlying root
epidermal differentiation. The network architecture includes two pathways;
one formed by the genes TTG, R homolog, GL2 and CPC, and the other one by t
he signal transduction proteins ETR1 and CTR1. Both parallel pathways regul
ate the activity of AXR2 and RHD6, which in turn control the development of
root hairs. The regulatory network was simulated as a dynamical system of
eight discrete state variables. The distinction between epidermal cells con
tacting one or two cortical cells was accounted for by fixing the initial s
tates of CPC and ETR1 proteins. The model allows for predictions of mutants
and pharmacological effects because it includes the ethylene receptor. The
dynamical system reaches one of the six stable states depending upon the i
nitial state of the CPC variable and the ethylene receptor. Two of the stab
le states describe the activation patterns observed in mature trichoblasts
(hair cells) and atrichoblasts (non-hair cells) in the wild-type phenotype
and under normal ethylene availability. The other four states correspond to
changes in the number of hair cells due to experimentally induced changes
in ethylene availability. This model provides a hypothesis on the interacti
ons among genes that encode transcription factors that regulate root hair d
evelopment and the proteins involved in the ethylene transduction pathway.
This is the first effort to use a dynamical system to understand the comple
x genetic regulatory interactions that rule Arabidopsis primary root develo
pment. The advantages of this type of models over static schematic represen
tations are discussed. (C) 2000 Academic Press.